AI / ML Engineer

Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Machine Learning Operations
Good to have skills : NA
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready application pipelines, ensuring high-quality standards are met. You will also explore the integration of generative AI models into solutions, while working on various aspects of deep learning, neural networks, chatbots, and image processing, contributing to innovative projects that push the boundaries of technology.
Role Summary
We are seeking a hands-on AI Native Engineer who can design, build, and deploy end-to-end agentic and LLM-powered systems. This includes constructing RAG pipelines, working with vector databases, building autonomous or semi-autonomous agents, integrating tools and skills, and developing evaluation frameworks for high-quality AI behaviour. You will prototype rapidly, experiment with models, and evolve solutions from PoC to production while working closely with cross-functional teams.
Key Responsibilities
Agentic & LLM System Development
Build agentic AI systems, including agent orchestration, planning loops, tool calling, and memory modules.
Implement LLM toolchains, custom prompts, templates, evaluators, and multi-step reasoning workflows.
Develop autonomous/semi-autonomous agents for retrieval, summarization, decision support, or workflow automation.
RAG Pipelines & Vector Intelligence
Design and implement RAG pipelines end-to-end: ingestion, chunking, embeddings, indexing, vector search, hybrid retrieval, and grounding.
Integrate vector databases such as pgvector, Pinecone, Weaviate, or Milvus.
Optimize retrieval quality, latency, and factual accuracy using rerankers, retrieval evaluators, and freshness pipelines.
Model Integration & AI Ops
Integrate enterprise-grade AI APIs, foundation models, and transformer models into scalable systems.
Implement robust evaluation frameworks including offline and online evals, regression tests, content safety checks, and red-team scenarios.
Build monitoring for model drift, agent failure modes, hallucination detection, and end-to-end system health.
Full-Stack & Cloud Alignment
Deploy services using Python/Node/Java microservices, serverless functions, or containerized workloads.
Integrate event streams, API gateways, and cloud-native patterns across Azure/AWS/GCP.
Build CI/CD pipelines for AI services with safe rollouts, versioning, and feature flags for model updates.
Prototyping & Rapid Iteration
Rapidly experiment with models, embeddings, architectures, and agentic patterns.
Translate business requirements into AI-native technical architectures and communicate trade-offs via demos and deep-dives.
Document designs, experiments, and evaluation results for reproducibility and knowledge sharing.
Professional & Technical Skills
Must-Have (AI Native Core)
Hands-on experience with LLMs, agent frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, AutoGen), and vector DBs.
Strong Python skills for building agents, RAG services, data pipelines, and evaluation harnesses.
Deep understanding of transformer models, embeddings, prompt engineering, and model fine-tuning workflows.
Experience deploying AI systems to production with monitoring, error handling, retries, and fallback strategies.
Good to Have
Experience with cloud AI platforms (Azure OpenAI, Bedrock, Vertex AI).
Knowledge of multimodal models, reinforcement learning, or advanced reasoning agents.
Familiarity with evaluation frameworks (pytest, JUnit) and custom eval harnesses.
Additional Information
Minimum 3 years of experience in ML/AI engineering (AI-native experience preferred).
Location: Bengaluru.
Education: 15 years full-time education.
Roles & Responsibilities:
- Expected to perform independently and become an SME.
- Required active participation/contribution in team discussions.
- Contribute in providing solutions to work related problems.
- Collaborate with cross-functional teams to gather requirements and translate them into technical specifications.
- Continuously evaluate and improve existing AI models and systems to enhance performance and efficiency.

Professional & Technical Skills:
- Must To Have Skills: Proficiency in Machine Learning Operations.
- Good To Have Skills: Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Strong understanding of machine learning algorithms and their applications.
- Experience in deploying machine learning models in production environments.
- Familiarity with data preprocessing and feature engineering techniques.

Additional Information:
- The candidate should have minimum 3 years of experience in Machine Learning Operations.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.

15 years full time education

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com 

Equal Employment Opportunity Statement

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.